76 citations · 149 across the 5 of their papers we have counts for
7 papers
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images
Adrian Galdran, José Dolz, Hadi Chakor +2
Assessing the degree of disease severity in biomedical images is a task similar to standard classification but constrained by an underlying structure in the label space. Such a str…
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
Adrian Galdran, André Anjos, José Dolz +3
The segmentation of the retinal vasculature from eye fundus images represents one of the most fundamental tasks in retinal image analysis. Over recent years, increasingly complex a…
Learned Pre-Processing for Automatic Diabetic Retinopathy Detection on Eye Fundus Images
Asim Smailagic, Anupma Sharan, Pedro Costa +3
Diabetic Retinopathy is the leading cause of blindness in the working-age population of the world. The main aim of this paper is to improve the accuracy of Diabetic Retinopathy det…
Self-supervised blur detection from synthetically blurred scenes
Aitor Alvarez-Gila, Adrian Galdran, Estibaliz Garrote +1
Blur detection aims at segmenting the blurred areas of a given image. Recent deep learning-based methods approach this problem by learning an end-to-end mapping between the blurred…
O-MedAL: Online Active Deep Learning for Medical Image Analysis
Asim Smailagic, Pedro Costa, Alex Gaudio +9
Active Learning methods create an optimized labeled training set from unlabeled data. We introduce a novel Online Active Deep Learning method for Medical Image Analysis. We extend…
Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis
Adrian Galdran, Aitor Alvarez-Gila, Maria Ines Meyer +7
Dermoscopic skin images are often obtained with different imaging devices, under varying acquisition conditions. In this work, instead of attempting to perform intensity and color…